Results 101 to 110 of about 40,034 (267)

Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN

Deep Underground Science and Engineering, EarlyView.
A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan, Chenxi Yin, Guangdong Yang, Shengyong Ding, Bin Tian   +4 more
wiley   +1 more source

From Ship to Shore: A Review of Vessel‐To‐Grid Bidirectional Charging for Sustainable Maritime Transport

EcoEnergy, EarlyView.
As maritime transport electrifies, bidirectional charging (V2G) offers a dual‐purpose solution for energy resilience and economic viability. This work identifies key technological advancements and lifecycle challenges utilizing practical case studies to demonstrate how V2G systems can drive decarbonization and grid stability in the marine sector ...
Jonathan Bloor, Tamer Kamel, Sarah Fear, Lee J. Durndell   +3 more
wiley   +1 more source

Bottlenecks‐Breaking in Zinc‐Iodine Batteries Toward Practical Implementation: A Review and Perspective

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
Aqueous zinc–iodine batteries (Zn–I2Bs) offer promise for grid storage due to safety and cost advantages yet face critical bottlenecks: severe self‐discharge (polyiodide shuttling and HER), limited energy density, sluggish kinetics, and zinc anode instability.
Jia‐Lin Yang, Jun‐Ming Cao, Dai‐Huo Liu, Xing‐Long Wu   +3 more
wiley   +1 more source

Entropy‐Driven Innovations: Entropy Stabilized Oxides for High‐Performance Next‐Generation Lithium–Sulfur Batteries

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
This article explores high‐entropy‐stabilized oxides (HEOs) as novel functional materials for addressing critical issues in lithium–sulfur (Li–S) batteries, including lithium polysulfide (LPS) shuttling, inadequate conductivity, and slow redox kinetics.
Hassan Raza, Jialiang Wei, Zhicai Wang, Zhaoyang Lv, Junye Cheng, Jia Xu, Liang An, Yuliang Liu, Sergey Ryazantsev, Shukui Li, Guangping Zheng   +10 more
wiley   +1 more source

AI‐based localization of the epileptogenic zone using intracranial EEG

Epilepsia Open, EarlyView.
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida, Yipeng Zhang, Sotaro Kanai, Richard Staba, Vwani Roychowdhury, Hiroki Nariai   +5 more
wiley   +1 more source

A Multivariate Mixed‐Effects Regression Framework for Ground Motion Modeling: Integrating Parametric and Machine Learning Approaches

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Multivariate ground motion models (GMMs) that capture the correlation between different intensity measures (IMs) are essential for seismic risk assessment. Conventional GMMs are often developed using a two‐stage approach, where separate univariate models with predefined functional forms are fitted first, and correlation is addressed in a ...
Sayed Mohammad Sajad Hussaini, Shaghayegh Karimzadeh, Paulo B. Lourenço   +2 more
wiley   +1 more source

Comparative Assessment and Benchmarking of Metaheuristic Algorithms for Dynamic Photovoltaic Array Reconfiguration Under Diverse Shading Environments

Energy Science &Engineering, EarlyView.
ABSTRACT The solar photovoltaic (PV) installations, which are essential for renewable energy systems, are vulnerable to partial shading, resulting in considerable power losses and operational inefficiencies. The dynamic reconfiguration of PV arrays has become an effective strategy to mitigate these effects by adaptively modifying the array topology to ...
Manoharan Premkumar, Ravichandran Sowmya, Jagarapu S. V. Siva Kumar, Mustafa Abdullah   +3 more
wiley   +1 more source

Hybrid Osprey‐Salp Swarm Optimization Algorithm for Single and Multiobjective Optimal Power Flow in Smart Grids With Renewable Energy Integration

Energy Science &Engineering, EarlyView.
The proposed hybrid osprey‐salp swarm optimization algorithm addresses optimal power flow (OPF) problems in smart grids incorporating solar, hydro, and thermal generators. The algorithm is validated on Institute of Electrical and Electronics Engineers 30‐, 57‐, and 118‐bus test systems across five single and multiobjective OPF scenarios.
Mujtaba Ali, Muhammad Yaqoob Javed, Aamer Bilal Asghar, Gang Xiong, Krzysztof Ejsmont, Xiaoli Liu   +5 more
wiley   +1 more source

Smart Charging With Hourly Pricing as Policy Intervention: Reducing Costs and Grid Congestion for Promoting Electric Vehicles in Developing Countries

Energy Science &Engineering, EarlyView.
Smart charging with hourly pricing optimizes electric vehicle (EV) charging in developing countries, reducing EV owner costs by 30% and easing grid congestion. Using an agent‐based energy management system, the study shows dynamic pricing effectively shifts charging to off‐peak hours, enhancing grid stability and supporting sustainable EV adoption in ...
Maha Iftikhar, Kashif Imran, Farah Ul Ain, Abdul Kashif Janjua, Rimsha Razaq, Sohail Khan, Arqam Ilyas, Shahbaz Ul Haq, Muhammad Akmal   +8 more
wiley   +1 more source

Decentralized Federated Learning for Wind Turbine Bearing Prognostics Under Data Scarcity and Statistical Heterogeneity

Energy Science &Engineering, EarlyView.
This paper proposes a decentralized peer‐to‐peer federated learning framework for wind turbine bearing remaining useful life prediction, introducing a virtual client paradigm in which statistical health indicators serve as independent feature‐level clients—enabling privacy‐preserving collaborative prognostics from a single physical asset under ...
Jihene Sidhom, Lotfi Saidi, Eric Bechhoefer   +2 more
wiley   +1 more source